UVR Lab. was formed
in Feb. 2001 at GIST to study and develop “Virtual Reality in Smart
computing environments” that process multimodal input, perceive
user’s intention and emotion, and respond to user’s request through
Augmented Reality. Since 2012, UVR Lab moved to KAIST GSCT and restarted
with a theme of “FUN in Ubiquitous VR.”

■ 연사:Kwang In Kim, Senior Lecturer, Department of Computer Science, University of Bath.

■ 일시: 07월 05일 (목) 오후 4시 (3시 30분부터 다과회)

■ 장소: KAIST KI빌딩 3층 교수회의실(D304호)

■ 주관: KAIST KI-ITC 증강현실연구센터(ARRC)

■ 후원: KAIST CT대학원, 한국HCI학회 DCH(디지털문화유산) 연구회, 대한전자공학회AH(증강휴먼) 연구회

■ 요약 :

Large databases are often organized by hand-labeled metadata, or criteria, which are expensive to collect. We can use unsupervised learning to model database variation, but these models are often high dimensional, complex to parameterize, or require expert knowledge.We learn low-dimensional continuous criteria via interactive ranking,so that the novice user need only describe the relative ordering of examples. This is formed as semi-supervised label propagation in whichwe maximize the information gained from a limited number of examples.Further, we actively suggest data points to the user to rank in a more informative way than existing work.In this talk, we will discuss our new semi-supervised and active regression learning strategies designedto address challenges in instantiating such systems.

**This lecture will be held in Korean. I apologize for announcing this information in Korean.